



'''simple docstring'''



import os
import re
import shutil
from argparse import ArgumentParser, Namespace

from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger


lowerCAmelCase_  :							List[Any]             =    '<<<<<<< This should probably be modified because it mentions: '

lowerCAmelCase_  :							List[Any]             =    '=======\n>>>>>>>\n'

lowerCAmelCase_  :							List[str]             =    [
    'TextEncoderConfig',
    'ByteTextEncoder',
    'SubwordTextEncoder',
    'encoder_config',
    'maybe_build_from_corpus',
    'manual_dir',
]

lowerCAmelCase_  :							Optional[int]             =    [
    # (pattern, replacement)
    # Order is important here for some replacements
    (R'tfds\.core', R'datasets'),
    (R'tf\.io\.gfile\.GFile', R'open'),
    (R'tf\.([\w\d]+)', R'datasets.Value(\'\1\')'),
    (R'tfds\.features\.Text\(\)', R'datasets.Value(\'string\')'),
    (R'tfds\.features\.Text\(', R'datasets.Value(\'string\'),'),
    (R'features\s*=\s*tfds.features.FeaturesDict\(', R'features=datasets.Features('),
    (R'tfds\.features\.FeaturesDict\(', R'dict('),
    (R'The TensorFlow Datasets Authors', R'The TensorFlow Datasets Authors and the HuggingFace Datasets Authors'),
    (R'tfds\.', R'datasets.'),
    (R'dl_manager\.manual_dir', R'self.config.data_dir'),
    (R'self\.builder_config', R'self.config'),
]
def        UpperCAmelCase (    A	:					Namespace					):
							return ConvertCommand(args.tfds_path       ,		args.datasets_directory					)






class 						lowerCamelCase_				(       snake_case_      ):







						@staticmethod
						def        __lowercase     (	lowerCAmelCase__ :   ArgumentParser					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   Tuple         =      parser.add_parser(
													    '''convert'''					,     help='''Convert a TensorFlow Datasets dataset to a HuggingFace Datasets dataset.'''					,     )
													train_parser.add_argument(
													    '''--tfds_path'''					,     type=lowerCAmelCase__					,     required=lowerCAmelCase__					,     help='''Path to a TensorFlow Datasets folder to convert or a single tfds file to convert.'''					,     )
													train_parser.add_argument(
													    '''--datasets_directory'''					,     type=lowerCAmelCase__					,     required=lowerCAmelCase__					,     help='''Path to the HuggingFace Datasets folder.'''					)
													train_parser.set_defaults(func=lowerCAmelCase__					)







						def __init__(	self :   List[str]					,     lowerCAmelCase__ :   str					,     lowerCAmelCase__ :   str					,     *lowerCAmelCase__ :   int					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   Tuple         =      get_logger('''datasets-cli/converting'''					)

													SCREAMING_SNAKE_CASE       :   int         =      tfds_path
													SCREAMING_SNAKE_CASE       :   List[Any]         =      datasets_directory







						def        __lowercase     (	self :   Any					):

													"""simple docstring"""
													if os.path.isdir(self._tfds_path					):
																				SCREAMING_SNAKE_CASE       :   Tuple         =      os.path.abspath(self._tfds_path					)
													elif os.path.isfile(self._tfds_path					):
																				SCREAMING_SNAKE_CASE       :   Dict         =      os.path.dirname(self._tfds_path					)
													else:
																				raise ValueError('''--tfds_path is neither a directory nor a file. Please check path.'''					)

													SCREAMING_SNAKE_CASE       :   Optional[Any]         =      os.path.abspath(self._datasets_directory					)

													self._logger.info(F"""Converting datasets from {abs_tfds_path} to {abs_datasets_path}"""					)

													SCREAMING_SNAKE_CASE       :   Tuple         =      []
													SCREAMING_SNAKE_CASE       :   int         =      []
													SCREAMING_SNAKE_CASE       :   Tuple         =      {}

													if os.path.isdir(self._tfds_path					):
																				SCREAMING_SNAKE_CASE       :   Any         =      os.listdir(lowerCAmelCase__					)
													else:
																				SCREAMING_SNAKE_CASE       :   int         =      [os.path.basename(self._tfds_path					)]

													for f_name in file_names:
																				self._logger.info(F"""Looking at file {f_name}"""					)
																				SCREAMING_SNAKE_CASE       :   Dict         =      os.path.join(lowerCAmelCase__					,     lowerCAmelCase__					)
																				SCREAMING_SNAKE_CASE       :   Any         =      os.path.join(lowerCAmelCase__					,     lowerCAmelCase__					)

																				if not os.path.isfile(lowerCAmelCase__					) or "__init__" in f_name or "_test" in f_name or ".py" not in f_name:
																											self._logger.info('''Skipping file'''					)
																											continue

																				with open(lowerCAmelCase__					,     encoding='''utf-8'''					) as f:
																											SCREAMING_SNAKE_CASE       :   Tuple         =      f.readlines()

																				SCREAMING_SNAKE_CASE       :   Optional[Any]         =      []
																				SCREAMING_SNAKE_CASE       :   Dict         =      False
																				SCREAMING_SNAKE_CASE       :   Tuple         =      False
																				SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      []
																				for line in lines:
																											SCREAMING_SNAKE_CASE       :   Optional[int]         =      line

																											# Convert imports
																											if "import tensorflow.compat.v2 as tf" in out_line:
																																		continue
																											elif "@tfds.core" in out_line:
																																		continue
																											elif "builder=self" in out_line:
																																		continue
																											elif "import tensorflow_datasets.public_api as tfds" in out_line:
																																		SCREAMING_SNAKE_CASE       :   Tuple         =      '''import datasets\n'''
																											elif "import tensorflow" in out_line:
																																		# order is important here
																																		SCREAMING_SNAKE_CASE       :   List[Any]         =      ''''''
																																		continue
																											elif "from absl import logging" in out_line:
																																		SCREAMING_SNAKE_CASE       :   Any         =      '''from datasets import logging\n'''
																											elif "getLogger" in out_line:
																																		SCREAMING_SNAKE_CASE       :   Tuple         =      out_line.replace('''getLogger'''					,     '''get_logger'''					)
																											elif any(expression in out_line for expression in TO_HIGHLIGHT					):
																																		SCREAMING_SNAKE_CASE       :   Dict         =      True
																																		SCREAMING_SNAKE_CASE       :   List[str]         =      list(filter(lambda lowerCAmelCase__					: e in out_line					,     lowerCAmelCase__					)					)
																																		out_lines.append(HIGHLIGHT_MESSAGE_PRE + str(lowerCAmelCase__					) + '''\n'''					)
																																		out_lines.append(lowerCAmelCase__					)
																																		out_lines.append(lowerCAmelCase__					)
																																		continue
																											else:
																																		for pattern, replacement in TO_CONVERT:
																																									SCREAMING_SNAKE_CASE       :   Any         =      re.sub(lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__					)

                # Take care of saving utilities (to later move them together with main script)
																											if "tensorflow_datasets" in out_line:
																																		SCREAMING_SNAKE_CASE       :   int         =      re.match(R'''from\stensorflow_datasets.*import\s([^\.\r\n]+)'''					,     lowerCAmelCase__					)
																																		tfds_imports.extend(imp.strip() for imp in match.group(1					).split(''','''					)					)
																																		SCREAMING_SNAKE_CASE       :   Optional[Any]         =      '''from . import ''' + match.group(1					)

																											# Check we have not forget anything
																											if "tf." in out_line or "tfds." in out_line or "tensorflow_datasets" in out_line:
																																		raise ValueError(F"""Error converting {out_line.strip()}"""					)

																											if "GeneratorBasedBuilder" in out_line or "BeamBasedBuilder" in out_line:
																																		SCREAMING_SNAKE_CASE       :   List[Any]         =      True
																											out_lines.append(lowerCAmelCase__					)

																				if is_builder or "wmt" in f_name:
																											# We create a new directory for each dataset
																											SCREAMING_SNAKE_CASE       :   Dict         =      f_name.replace('''.py'''					,     ''''''					)
																											SCREAMING_SNAKE_CASE       :   Any         =      os.path.join(lowerCAmelCase__					,     lowerCAmelCase__					)
																											SCREAMING_SNAKE_CASE       :   Any         =      os.path.join(lowerCAmelCase__					,     lowerCAmelCase__					)
																											os.makedirs(lowerCAmelCase__					,     exist_ok=lowerCAmelCase__					)
																											self._logger.info(F"""Adding directory {output_dir}"""					)
																											imports_to_builder_map.update({imp: output_dir for imp in tfds_imports}					)
																				else:
																											# Utilities will be moved at the end
																											utils_files.append(lowerCAmelCase__					)

																				if needs_manual_update:
																											with_manual_update.append(lowerCAmelCase__					)

																				with open(lowerCAmelCase__					,     '''w'''					,     encoding='''utf-8'''					) as f:
																											f.writelines(lowerCAmelCase__					)
																				self._logger.info(F"""Converted in {output_file}"""					)

													for utils_file in utils_files:
																				try:
																											SCREAMING_SNAKE_CASE       :   Any         =      os.path.basename(lowerCAmelCase__					)
																											SCREAMING_SNAKE_CASE       :   str         =      imports_to_builder_map[f_name.replace('''.py'''					,     ''''''					)]
																											self._logger.info(F"""Moving {dest_folder} to {utils_file}"""					)
																											shutil.copy(lowerCAmelCase__					,     lowerCAmelCase__					)
																				except KeyError:
																											self._logger.error(F"""Cannot find destination folder for {utils_file}. Please copy manually."""					)

													if with_manual_update:
																				for file_path in with_manual_update:
																											self._logger.warning(
																											    F"""You need to manually update file {file_path} to remove configurations using 'TextEncoderConfig'."""					)









'''simple docstring'''



import os

lowerCAmelCase_  :							Union[str, Any]             =    {'I': 1, 'V': 5, 'X': 10, 'L': 50, 'C': 100, 'D': 500, 'M': 1000}
def        UpperCAmelCase (    A	:					str					):
							SCREAMING_SNAKE_CASE       :   str         =      0

							SCREAMING_SNAKE_CASE       :   List[str]         =      0
							while index < len(A					) - 1:
														SCREAMING_SNAKE_CASE       :   Dict         =      SYMBOLS[numerals[index]]
														SCREAMING_SNAKE_CASE       :   str         =      SYMBOLS[numerals[index + 1]]
														if current_value < next_value:
																					total_value -= current_value
														else:
																					total_value += current_value
														index += 1
							total_value += SYMBOLS[numerals[index]]

							return total_value
def        UpperCAmelCase (    A	:					int					):
							SCREAMING_SNAKE_CASE       :   Any         =      ''''''

							SCREAMING_SNAKE_CASE       :   Dict         =      num // 1000
							numerals += m_count * "M"
							num %= 1000

							SCREAMING_SNAKE_CASE       :   str         =      num // 100
							if c_count == 9:
														numerals += "CM"
														c_count -= 9
							elif c_count == 4:
														numerals += "CD"
														c_count -= 4
							if c_count >= 5:
														numerals += "D"
														c_count -= 5
							numerals += c_count * "C"
							num %= 100

							SCREAMING_SNAKE_CASE       :   Any         =      num // 10
							if x_count == 9:
														numerals += "XC"
														x_count -= 9
							elif x_count == 4:
														numerals += "XL"
														x_count -= 4
							if x_count >= 5:
														numerals += "L"
														x_count -= 5
							numerals += x_count * "X"
							num %= 10

							if num == 9:
														numerals += "IX"
														num -= 9
							elif num == 4:
														numerals += "IV"
														num -= 4
							if num >= 5:
														numerals += "V"
														num -= 5
							numerals += num * "I"

							return numerals
def        UpperCAmelCase (    A	:					str = "/p089_roman.txt"					):
							SCREAMING_SNAKE_CASE       :   List[str]         =      0

							with open(os.path.dirname(A					) + roman_numerals_filename					) as filea:
														SCREAMING_SNAKE_CASE       :   str         =      filea.readlines()

							for line in lines:
														SCREAMING_SNAKE_CASE       :   Any         =      line.strip()
														SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      parse_roman_numerals(A					)
														SCREAMING_SNAKE_CASE       :   Any         =      generate_roman_numerals(A					)
														savings += len(A					) - len(A					)

							return savings


if __name__ == "__main__":
							print(f'{solution() = }')




